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Clustering Patients with Tensor Decomposition
In this paper we present a method for the unsupervised clustering of high-dimensional binary data, with a special focus on electronic healthcare records. We present a robust and efficient heuristic to face this problem using tensor decomposition. We present the reasons why this approach is preferabl...
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Published in: | arXiv.org 2017-08 |
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creator | Ruffini, Matteo Gavaldà, Ricard Limón, Esther |
description | In this paper we present a method for the unsupervised clustering of high-dimensional binary data, with a special focus on electronic healthcare records. We present a robust and efficient heuristic to face this problem using tensor decomposition. We present the reasons why this approach is preferable for tasks such as clustering patient records, to more commonly used distance-based methods. We run the algorithm on two datasets of healthcare records, obtaining clinically meaningful results. |
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subjects | Algorithms Binary data Clustering Decomposition Electronic health records Health care Mathematical analysis Tensors |
title | Clustering Patients with Tensor Decomposition |
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